Title :
Study of Coupling Based on Genetic Neural Network Multivariable Nonlinear Complex System
Author :
Gong, Ruikun ; Li, Jingyuan ; Chen, Lei
Author_Institution :
Coll. of Comput. & Autom. Control, Hebei Polytech. Univ., Tangshan
Abstract :
In this paper a method of decoupling has been put forward. Combine genetic neural network with multivariable nonlinear system adaptive decoupling control algorithm. Establish a control model of multivariable parameter in order to cancel the couplings of various variables. This method improves the stability and precision. According to the METLAB emulator proving, genetic neural network multivariable nonlinear decoupling model can cancel multivariable coupling problem preferably, make the system optimized.
Keywords :
adaptive control; genetic algorithms; multivariable control systems; neurocontrollers; nonlinear control systems; stability; METLAB; adaptive decoupling control; genetic neural network; multivariable nonlinear complex system; multivariable nonlinear decoupling model; Adaptive control; Adaptive systems; Control systems; Couplings; Genetics; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Stability; decoupling; genetic neural network; multivariable; nonlinear;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.612
